ECTS - University of Pisa
Scheda programma d'esame
Computational Materials Science
GIUSEPPE BRANCATO
Academic year2023/24
CourseMATERIALS AND NANOTECHNOLOGY
Code311CC
Credits6
PeriodSemester 1
LanguageEnglish

ModulesAreaTypeHoursTeacher(s)
COMPUTATIONAL MATERIALS SCIENCEING-IND/22LEZIONI48
GIUSEPPE BRANCATO unimap
Programma non disponibile nella lingua selezionata
Learning outcomes
Knowledge

 

- Providing a basic theoretical ground for the comprehension of molecular modeling techniques currently used in the field of life and material sciences

- Developing competencies in some of the most common computational methodologies used in molecular sciences

- Developing computational skills through tutorials and exercises 

- Stimulating the students to study a scientific problem of their interest suitable to be treated with molecular modeling methodologies
Assessment criteria of knowledge

Knowledge will be assessed via:

  • ongoing assignments
  • final oral exam
Skills

After the completion of the course, the students will be able to:

  • Demonstrate effective communication skills through scientific presentations and reports
  • Demonstrate the capability of understanding the scientific literature.
Assessment criteria of skills

Skills will be assessed via:

  • ongoing group assignments
  • final oral exam
Behaviors

After the completion of the course, the students will be able to:

  • understand the main computational methodologies used to study molecular systems.
  • suggest a scientific problem of their interest suitable to be treated with molecular modeling methodologies.
  • develop basic computational skills in molecular modeling through computational exercises.
Assessment criteria of behaviors

Behaviors will be assessed via:

  • ongoing group assignments
  • final oral exam
Prerequisites

Prerequisites: Basic undergraduate courses in Physics, Chemistry, and Biology.
Teaching methods

The teaching is based on lectures, exercises, and teamwork. Teaching material is provided through the class website on the institutional platform.
Syllabus

The aim of the course is to provide an overview of the theories and methodologies currently used in various fields of computational molecular sciences, ranging from biomedical sciences to material sciences. A special focus will be devoted to those models and algorithms related to molecular simulation techniques, including enhanced sampling and free energy methods. Such models will be illustrated along with relevant examples taken from recent literature concerning different molecular modeling applications. 

 

 

 
Bibliography

Molecular Modelling: Principles and Applications (2nd Edition), Leach

Understanding Molecular Simulation, Second Edition: From Algorithms to Applications (Computational Science) 2nd Edition, Frenkel

Additional articles and reference material will be provided in class.
Non-attending students info

Contact the teacher for the didactical material and course information.
Updated: 05/07/2024 11:17